Triple

T13613955
Position Surface form Disambiguated ID Type / Status
Subject Mississippi Girl E325262 entity
Predicate mainCharacter P1183 FINISHED
Object Faith Hill persona E64047 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Faith Hill persona | Statement: [Mississippi Girl, mainCharacter, Faith Hill persona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faith Hill persona
Context triple: [Mississippi Girl, mainCharacter, Faith Hill persona]
  • A. Faith Hill chosen
    Faith Hill is an American country and pop singer known for her powerful vocals, crossover hits, and multiple Grammy Awards.
  • B. Loretta
    Loretta is a feminine given name of Latin origin, often associated with the laurel tree and borne by various notable figures.
  • C. Lana Michele Moorer
    Lana Michele Moorer is an American rapper, DJ, and actress best known by her stage name MC Lyte, a pioneering figure in hip hop and one of the first prominent female MCs.
  • D. Pam Tillis
    Pam Tillis is an American country music singer-songwriter and actress known for hits in the 1990s such as "Maybe It Was Memphis" and "Mi Vida Loca (My Crazy Life)."
  • E. Lorrie Morgan
    Lorrie Morgan is an American country music singer known for her emotive vocal style and a string of hits since the late 1980s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0abe1208190a1e0a32dc141d836 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f9cbc388190972e949324144d2f completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.